Sangam: A Confluence of Knowledge Streams

Extracting capacity metrics for General Aviation airports from ADS-B data

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dc.contributor Lovell, David J
dc.contributor Digital Repository at the University of Maryland
dc.contributor University of Maryland (College Park, Md.)
dc.contributor Civil Engineering
dc.creator Mitkas, Danae Zoe
dc.date 2021-07-15T05:30:58Z
dc.date 2021-07-15T05:30:58Z
dc.date 2021
dc.date.accessioned 2022-05-20T08:38:49Z
dc.date.available 2022-05-20T08:38:49Z
dc.identifier https://doi.org/10.13016/ayvx-lfqr
dc.identifier http://hdl.handle.net/1903/27505
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/117660
dc.description General Aviation airports play a pivotal role in the aviation system of the US, with over 5000 small airports existing and operating across the country. Serving almost exclusively small aircraft, these airports have a unique activity profile, compared to larger commercial airports. Like their larger cousins, they occasionally see the need to apply for federal funding for capacity enhancement projects, a process that requires rigorous documentation of the demand and capacity situation at the airport. Existing models for capacity estimation have been calibrated to reflect the much larger scale features that dominate large airports. The main challenge is to develop a method to provide precise data for small airports that operate mainly with small single or multi-engine aircraft. These airports are typically not towered and, hence, do not benefit from traditional automated data collection technologies. This research addresses the issues of a) collecting aircraft data at local airport environments from aircraft equipped with Automated Dependent Surveillance – Broadcast (ADS-B) technology, b) processing the data to determine and classify flights, and c) assessing elements of the operational performance of these aircraft. The thesis proposes a method to extract aircraft approach speeds and runway occupancy times, which are important contributors to capacity estimation. We applied and validated our method in three small airports.
dc.format application/pdf
dc.language en
dc.subject Civil engineering
dc.subject Transportation
dc.subject ADS-B
dc.subject Aviation
dc.subject Capacity
dc.subject General Aviation airports
dc.title Extracting capacity metrics for General Aviation airports from ADS-B data
dc.type Thesis


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